According to the prior art, people handle daily affairs efficiently, thanks to modern image processing technology. For example, bus terminals along highways are usually installed with an image processing and recognition system based on conventional image processing technology and adapted to monitor the arrival and departure of a plurality of buses. A conventional method for monitoring the traffic attributed to the buses entails recognizing license plate numbers of the buses using the conventional image processing technology.
At present, at plenty of highway bus terminals, license plate numbers are detected and recognized with the conventional image processing recognition system.
However, in the course of recognizing the license plate numbers, recognition failures are not uncommon.
Hence, the conventional image processing and recognition system applies character recognition technology, such as optical character recognition (OCR), in recognizing the license plate numbers of the license plates. However, during the process of recognizing the license plate numbers in accordance with the character recognition technology, the images of the license plate numbers have to be sharp in order for the license plate numbers to be recognized.
Furthermore, in the course of the license plate number recognition, recognition of the license plate numbers fails or is unsatisfactory for intrinsic reasons and extrinsic reasons. The intrinsic reasons include concealment of the license plate, dirt and dust on the license plate, and the situation where the license plate number printed on the license plate is blurred. The extrinsic reasons include inadequate illumination, glare arising from smog reflection, and blinding headlight.
Still, the aforesaid problems which occur for the intrinsic reasons and extrinsic reasons have remained unsolved.
In attempt to solve the aforesaid problems, the prior art puts forth some solutions, including performing license plate recognition in two step. The first step involves capturing an image of the license plate. The second step involves recognizing the license plate number. The license plate image capturing step requires computing license plate images with a license plate outline algorithm, a color distribution algorithm, or a grayscale distribution algorithm in order to evaluate regional distribution of the license plates. The license plate number recognition step involves recognizing the license plate number with a character recognition algorithm.
However, regardless of the algorithm used, the aforesaid prior art has to meet a criterion—to recognize a license plate number, the image of the license plate which bears the license plate number has to be sharp and recognizable.
Accordingly, it is imperative to provide a license plate recognition system and method in order to overcome the aforesaid drawbacks of the prior art.